Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Introduction:
The convenience of online food ordering has rapidly grown in popularity in recent years, as
technology has made it easier for people to access and purchase food from their favourite restaurants
without leaving their homes. To understand the trend and preferences of online food ordering, a
survey was conducted to gather insights from a sample of consumers. The following report presents
an analysis of the survey responses and provides a comprehensive overview of the findings on the
topic of online food ordering.
Objectives of the Survey:
The objective of this survey was to examine the habits and attitudes of individuals towards online
food ordering. The survey aimed to collect data on the frequency of online food ordering, the type of
food ordered, the level of due diligence conducted by the respondents while ordering food, the impact
of online food ordering on overall food consumption, and the perceived advantages and disadvantages
of ordering food online. By gathering insights into these areas, the survey aimed to provide a
comprehensive overview of the trend of online food ordering and its impact on individual consumers.
Questions asked in the Survey:
1.
2.
3.
4.
How many times do you order food using online platforms? (Q1)
Do you order fast food? (Q2)
Do you order Health Food? (Q3)
Have you visited the restaurants from where you order food online to ascertain cleanliness of
the kitchen and the staff? (Q4)
5. When you order Fast food do you check the percentage of fat and Sugar content in the food?
(Q5)
6. When you order Health food do you verify if the contents added to make the food are as per
the claims made by the vendors? (Q6)
7. Your Age? (Q7)
8. Do you think that you are consuming more food every week by including online food? (Q8)
9. Do you feel that ordering food via online platforms has a distinct advantage of not having to
commute or wait at the restaurant amongst a crowd of people? (Q9)
10. Does your over all food bills increase due to online ordering? (Q10)
Methodology: Survey Administration and Sample Size:
The survey was conducted online and administered through snowball sampling. A total of 287
respondents participated in the survey, consisting of two groups with 54 and 233 participants
respectively.
Data Analysis: Chi-Square Test and Confidence Interval Estimation
Performing a chi-square test on survey responses and estimating confidence intervals are important
steps in analysing and interpreting the results of a survey. The chi-square test helps to determine if
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
there is a significant relationship between two categorical variables, such as the type of food ordered
and the frequency of online ordering. Confidence intervals provide a range of values that are likely to
contain the true population mean with a certain level of confidence. By estimating confidence
intervals, it is possible to extrapolate the sample statistics to the larger population, making it possible
to generalize the findings of the survey to a wider audience."
Analysis of Survey Results:
1. How many times do you order food using online platforms?
Answer Choice
Morsel
Survey
Survey
Monkey
%age 1
% age 2
Combined
Less than three times a month
78
30
33.48
55.56
37.63
Between 3 and 7 times a
month
Between 8 and 15 times a
month
Between 15 and 30 times a
month
77
9
33.05
16.67
29.97
39
4
16.74
7.41
14.98
19
8
8.15
14.81
9.41
Between 30 and 50 times a
month
5
1
2.15
1.85
2.09
More than 50 times a month
5
0
2.15
0
1.74
Others
10
2
4.29
3.7
4.18
233
54
287
The above table shows data on the frequency of ordering food using online platforms, as gathered
from two surveys - Morsel Survey and Survey Monkey. The table shows the number of respondents
and the percentage of respondents who answered each of the given answer choices. In total, there
were 287 respondents who participated in both surveys. According to the data, the most common
frequency of ordering food online is less than three times a month, with 37.63% of respondents
selecting this option. The next most common frequency is between 3 and 7 times a month, selected by
29.97% of respondents. The data also shows that a small percentage of respondents’ order food online
very frequently. Only 2.09% of respondents order between 30 and 50 times a month, and just 1.74%
of respondents order more than 50 times a month. Finally, a small percentage of respondents selected
"others" as their answer choice, which may indicate that they order food online at irregular
frequencies or have some other specific ordering pattern. The same is shown as a pie chart in the
figure below.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Frequency of ordering food (Percentage)
1.74
4.18
2.09
9.41
37.63
14.98
29.97
Less than three times a month
Between 3 and 7 times a month
Between 8 and 15 times a month
Between 15 and 30 times a month
Between 30 and 50 times a month
More than 50 times a month
Others
2. Do you order fast food?
Answer
Morsel
Choice
Survey
Survey
Monkey
% age 1
% age 2
Combined
Yes
Sometimes
145
33
62.23
61.11
62.02
Never
28
17
12.02
31.48
15.68
Always
60
4
25.75
7.41
22.3
233
54
100
100
100
The above table shows data on whether or not respondents order fast food, as gathered from two
surveys - Morsel Survey and Survey Monkey. The table displays the number of respondents and the
percentage of respondents who selected each answer choice. In total, there were 287 respondents who
participated in both surveys. The data reveals that the majority of respondents order fast food, with
62.02% of respondents selecting "Yes, sometimes" as their answer choice. The data also shows that a
significant number of respondents always order fast food, with 22.30% of respondents selecting
"Always". On the other hand, a smaller percentage of respondents never order fast food, with 15.68%
of respondents selecting "Never". It is interesting to note that the percentage of respondents who
always order fast food is significantly higher in the Morsel survey (25.75%) than in the Survey
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Monkey survey (7.41%). This may be due to the fact that the respondents in the two surveys may
differ in terms of demographics or other factors that influence their eating habits. Overall, the data
suggests that a significant number of people order fast food, and that fast food is a popular option for
many people. The same is shown as a pie chart in the figure below.
Do you order fast food (responses in percentage)
22.3
15.68
62.02
Yes Sometimes
3. Do you order Health Food?
Answer Choice
Never
Always
Morsel
Survey
Survey % age 1
Monkey
% age 2
Combined
I only order Health Food
116
4
49.79
7.41
41.81
I order Health Food a majority
of times
51
9
21.89
16.67
20.91
I order Health food on a few
occasions
45
25
19.31
46.3
24.39
I never order Health food
21
16
9.01
29.63
12.89
233
54
100
100.01
100
The above table shows the results of a survey on whether people order health food. The survey was
conducted by two different methods: Morsel Survey and Survey Monkey, and the percentages for
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
each answer choice are provided separately for each method, as well as the combined percentages.
There are four answer choices:
"I only order Health Food”, “I order Health Food a majority of times”, “I order Health food on a few
occasions" "I never order Health food". The data shows that out of the 233 total respondents, 116
(49.79% on Morsel Survey and 7.41% on Survey Monkey) said they only order health food, while 51
(21.89% on Morsel Survey and 16.67% on Survey Monkey) said they order health food a majority of
the time. 45 respondents (19.31% on Morsel Survey and 46.3% on Survey Monkey) said they order
health food on a few occasions, while 21 (9.01% on Morsel Survey and 29.63% on Survey Monkey)
said they never order health food. The combined percentages are also provided, and they show that
41.81% of respondents only order health food, 20.91% order health food a majority of the time,
24.39% order health food on a few occasions, and 12.89% never order health food. Overall, the data
suggests that a significant percentage of respondents order health food to some extent, with nearly
63% of respondents saying they order health food either exclusively or a majority of the time. The
same is shown in the figure below.
Do you order health food? (Responses in percentage)
12.89
41.81
24.39
20.91
I only order Health Food
I order Health Food a majority of times
I order Health food on a few occasionsI never order Health food
Q4. Have you visited the restaurants from where you order food online in order to ascertain
cleanliness of the kitchen and the staff?
Answer
Choice
Morsel
Survey
Survey
Monkey
% age 1
% age 2
Combined
Yes
141
30
60.52
55.56
59.58
No
92
24
39.48
44.44
40.42
233
54
100
100
100
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on the topic of whether individuals who order food online have visited the restaurants to
check the cleanliness of the kitchen and staff. The combined data shows that out of 233 respondents,
141 individuals (60.52% from Morsel Survey and 55.56% from Survey Monkey) have visited the
restaurants, while 92 individuals (39.48% from Morsel Survey and 44.44% from Survey Monkey)
have not. It is worth noting that the percentage of individuals who have visited the restaurants is
slightly higher in the Morsel Survey than in the Survey Monkey survey. However, the overall
combined percentage of those who have visited the restaurants is 59.58%. Based on this data, it can
be inferred that a significant proportion of individuals who order food online have visited the
restaurants to check the cleanliness of the kitchen and staff. However, a substantial proportion have
not. It is unclear why individuals have chosen not to visit the restaurants, but factors such as
convenience, trust in online reviews, or lack of time could be possible reasons. This is shown in the
pie chart below.
Have you visited the restaurants from where you order food
online in order to ascertain cleanliness of the kitchen and the
staff? (Reponses in percentage)
40.42
59.58
Yes
No
Question 5: When you order Fast food do you check the percentage of fat and Sugar content in the
food?
Answer Choice
Morsel
Survey
Survey
Monkey
Percentage 1
Percentage 2
Combined
Never
44
32
18.88
59.26
26.48
Always
151
6
64.81
11.11
54.7
Sometimes when it
Is declared in the
menu
38
16
16.31
29.63
18.82
233
54
100
100
100
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on the topic of whether individuals who order fast food check the percentage of fat and sugar
content in the food. The combined data shows that out of 233 respondents, 151 individuals (64.81%
from Morsel Survey and 11.11% from Survey Monkey) always check the percentage of fat and sugar
content in the food. In addition, 38 individuals (16.31% from Morsel Survey and 29.63% from Survey
Monkey) sometimes check the percentage when it is declared in the menu. Finally, 44 individuals
(18.88% from Morsel Survey and 59.26% from Survey Monkey) never check the percentage of fat
and sugar content in the food. It is worth noting that the percentage of individuals who always check
the percentage of fat and sugar content in the food is higher in the Morsel Survey than in the Survey
Monkey survey. However, the overall combined percentage of those who always check or sometimes
check the percentage is 73.52%. Based on this data, it can be inferred that a significant proportion of
individuals who order fast food check the percentage of fat and sugar content in the food. However, a
considerable proportion do not check at all. It is possible that individuals who do not check the
percentage may prioritize taste, convenience, or price over nutrition. On the other hand, individuals
who always or sometimes check the percentage may be more health-conscious or have specific
dietary requirements. This is shown in the figure below.
When you order Fast Food do you check the percentage of Fat
and Sugar content in the food?
26.48
100
54.7
18.82
Never
Always
Sometimes when it Is declared in the menu
Question 6: When you order Health food do you verify if the contents added to make the food are as
per the claims made by the vendors?
Answer
Choice
Morsel
Survey
Survey
Monkey
Percentage 1 Percentage 2 Combined
Never
32
31
13.73
57.41
21.95
Sometimes
151
21
64.81
38.89
59.93
Always
50
2
21.46
3.7
18.12
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
233
54
100
100
100
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on the topic of whether individuals who order health food verify if the contents added to
make the food are as per the claims made by the vendors. The combined data shows that out of 233
respondents, 151 individuals (64.81% from Morsel Survey and 38.89% from Survey Monkey)
sometimes verify if the contents added to make the food are as per the claims made by the vendors. In
addition, 50 individuals (21.46% from Morsel Survey and 3.7% from Survey Monkey) always verify
if the contents added to make the food are as per the claims made by the vendors. Finally, 32
individuals (13.73% from Morsel Survey and 57.41% from Survey Monkey) never verify if the
contents added to make the food are as per the claims made by the vendors.
It is worth noting that the percentage of individuals who always verify the contents is higher in the
Morsel Survey than in the Survey Monkey survey. However, the overall combined percentage of
those who always verify or sometimes verify is 80.05%. Based on this data, it can be inferred that a
significant proportion of individuals who order health food verify if the contents added to make the
food are as per the claims made by the vendors. However, a considerable proportion do not verify at
all. It is possible that individuals who do not verify may trust the vendors' claims or may not be aware
of the importance of verifying. On the other hand, individuals who always or sometimes verify may
be more health-conscious or have specific dietary requirements. This is shown in the figure below.
When you order Health food do you verify if the contents added
to make the food are as per the claims made by the vendors?
21.95
100
59.93
18.12
Never
Sometimes
Always
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on the age of the respondents. The combined data shows that out of 233 respondents, the
majority of the respondents are in the age group between 20 and 40 years old. Specifically, 101
individuals (43.35% from Morsel Survey and 12.96% from Survey Monkey) are between 20 and 30
years old, and 74 individuals (31.76% from Morsel Survey and 24.07% from Survey Monkey) are
between 30 and 40 years old. The age group less than 20 years old and the age group between 40 and
50 years old have the lowest number of respondents. The age group between 50 and 60 years old has
the second-highest number of respondents, with 17 individuals (0.43% from Morsel Survey and
29.63% from Survey Monkey) falling in this age range. Finally, the age group above 60 years old has
the lowest number of respondents, with 4 individuals (1.72% in total) falling in this age range. This is
shown in the figure below.
Combined
18.47
37.63
99.99
30.31
1.39
5.92
6.27
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 years old
Between 50 and 60 years old
Above 60 years old
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Q8: Do you think that you are consuming more food every week by including online food?
Answer Choice
Yes
No
Total intake remains the
same
Not sure
Morsel
Survey
136
Survey
Monkey
14
% age 1
% age 2
Combined
58.37
25.93
52.26
77
14
24
12
33.05
6.01
44.44
22.22
35.19
9.06
6
4
2.58
7.41
3.48
233
54
100.01
100
99.99
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on whether respondents think they consume more food every week by including online food.
The combined data shows that out of 233 respondents, a slight majority of 52.26% think they
consume more food every week by including online food, while 35.19% think they do not consume
more food, and 9.06% believe their total intake remains the same. The remaining 3.48% of
respondents are not sure.
It is worth noting that the percentage of individuals who believe they consume more food every week
by including online food varies between the Morsel Survey and the Survey Monkey survey. Morsel
Survey has a higher percentage of respondents who think they consume more food than the Survey
Monkey survey. On the other hand, the Survey Monkey survey has a higher percentage of
respondents who are not sure. Based on this data, it can be inferred that a slight majority of the
respondents believe they consume more food every week by including online food, but there are still
a significant number of respondents who do not think they consume more food. The data may suggest
that the availability and ease of online food ordering may lead to some people consuming more food
than they otherwise would, but it is not a universal trend among all online food consumers. This is
shown in the figure below.
Are you consuming more food due to online Ordering?
52.26
99.99
35.19
3.48
Yes
No
9.06
Total intake remains the same
Not sure
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Question 9: Do you feel that ordering food via online platforms has a distinct advantage of not having
to commute or wait at the restaurant amongst a crowd of people?
Answer
Choice
No
Morsel
Survey
92
Survey
Monkey
14
Percentage 1
Percentage 2
Combined
39.48
25.93
36.93
Yes
141
40
60.52
74.07
63.07
233
54
100
100
100
The above table presents data from two different surveys conducted by Morsel Survey and Survey
Monkey on whether respondents feel that ordering food via online platforms has a distinct advantage
of not having to commute or wait at the restaurant amongst a crowd of people. The combined data
shows that out of 233 respondents, a majority of 63.07% feel that ordering food via online platforms
has the distinct advantage of not having to commute or wait at the restaurant amongst a crowd of
people, while 36.93% do not feel that way. It is worth noting that the percentage of individuals who
feel that ordering food via online platforms has a distinct advantage of not having to commute or wait
at the restaurant amongst a crowd of people varies significantly between the Morsel Survey and the
Survey Monkey survey. Survey Monkey has a much higher percentage of respondents who feel that
way than the Morsel Survey. Based on this data, it can be inferred that a majority of the respondents
feel that ordering food via online platforms has the distinct advantage of not having to commute or
wait at the restaurant amongst a crowd of people. This suggests that convenience is a major factor
driving the popularity of online food ordering, and it is a key benefit that consumers perceive from a
mode of food consumption. This is shown in the following figure
Does ordering food online have a distinct advantage?
36.93
100
63.07
No
Yes
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Q10: Does your over all food bill increase due to online ordering?
Answer Choice
Morsel Survey
% age 1
% age 2
Survey Monkey
No, it has not
118
9
50.64
16.67
increased
Have not made an
40
11
17.17
20.37
attempt to verify
It has increased by a 51
14
21.89
25.93
small percentage
It has increased by a 18
14
7.73
25.93
moderate percentage
It has increased
6
6
2.58
11.11
significantly
233
54
100.01
100.01
Combined
44.25
17.77
22.65
11.15
4.18
100
The above table shows the responses to the question "Does your overall food bill increase due to
online ordering?" from two different surveys. In the Morsel Survey, 118 respondents (50.64%)
answered that their overall food bill has not increased due to online ordering. 51 respondents
(21.89%) reported a small increase, 18 (7.73%) reported a moderate increase, and 6 (2.58%) reported
a significant increase. 40 respondents (17.17%) said they have not made an attempt to verify. In the
Survey Monkey, 9 respondents (16.67%) answered that their overall food bill has not increased due to
online ordering. 11 respondents (20.37%) reported that they have not made an attempt to verify. 14
respondents (25.93%) reported a small increase, and 14 respondents (25.93%) reported a moderate
increase. 6 respondents (11.11%) reported that it has increased significantly. Overall, the majority of
respondents from both surveys reported that their overall food bill has either not increased or has only
increased by a small percentage due to online ordering. This is shown in the figure below
Combined
44.25
100
No, it has not increased
It has increased by a small percentage
It has increased significantly
:
17.77
22.65
4.18 11.15
Have not made an attempt to verify
It has increased by a moderate percentage
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Data Analysis and Results: Contingency Tables, Graphs and Chi-Square Test
From the data received on the survey of 10 multiple-choice questions (classification), the
independence of the results was evaluated using contingency tables with two classification criteria
and the chi-square test. Details about the chi square tests can be viewed after the summary section
presented immediately below/
The results summarized in findings are shown below.
1.Frequency of Ordering food online vs Age of respondent (Q1 vs Q7): The chi square result
indicates that the frequency of food using platforms orders is age-dependent, which is clearly seen in
the figure. -86% of the orders are placed by respondents under 40 years old. Seventy-one percent of
these respondents (<40 years old) order with a maximum frequency of 15 times per month. The data
shows that individuals aged between 20- and 30-years old order food the most frequently, with 38
percent individuals in that age range, while individuals above 60 years old order food the least
frequently, with only 2 percent of all the respondents.
2.Frequency of ordering fast food vs Age of Respondent (Q2 vs Q7): The chi square result indicates
that fast food orders are age-dependent, which is clearly observed in the figure.
-84%t of the respondents sometimes or always order fast food. Seventy-seven percent of this group is
under 40 years of age. Refer Figure 2. This table shows the distribution of individuals who order fast
food (Q2) based on their age (Q7). The table displays the percentage of individuals who answered
"yes", "sometimes", "never" and "missing". The data shows that 62% of the total individuals
answered "yes" to ordering fast food, while 22% answered "never". Individuals aged between 20 and
30 years old have the highest percentage of individuals who order fast food, with 23% of individuals
in that age range answering "yes". Individuals above 60 years old have the lowest percentage of
individuals who order fast food, with only 1% of individuals in that age range answering "yes".
3.Frequency of ordering health food vs Age of Respondent (Q3 vs Q7): The chi square result
indicates that health food orders are age-dependent, as clearly seen in Figure 3.
-13% of respondents never order health food, 87% order health food occasionally or more frequently.
-56% order only or mostly health food and are under 40 years of age. Those older than 40 years order
only or mostly in 6% of cases.
4.
Have you visited the restaurants…cleanliness vs Age of respondent (Q4 vs Q7): The result of
chi square indicates that visits to restaurants are independent of the age of the respondents.
Visits to restaurants turned out to be independent of age. 60% visit the restaurants from where they
order food online in order to ascertain of the kitchen and the staff. 42% are aged between 20 to 40
years old. 40 percent or 115 respondents out of 287 do not visit the restaurants directly to verify the
cleanliness.
5.
When you order Fast food…percentage vs Age of Respondent (Q5 vs Q7): The chi square
result indicates that there is insufficient statistical evidence to ensure that the percentage of fat and
sugar check is age dependent. The graph shows that the highest percentage of checking corresponds
to respondents up to 40 years of age. -4% sometimes or always check the percentage of fat and sugar
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
when they order fast food. 42% are under 40 years of age. -26% never check fat and sugar
percentages.
When ordering fast food online without checking the fat and sugar content, there are several potential
risks to consider, including:
Health: Consuming food that is high in fat and sugar can increase the risk of obesity, heart disease,
and other health problems. This is especially true if you are consuming fast food frequently.
Unbalanced Diet: Fast food is often lacking in essential vitamins and nutrients, which can lead to an
unbalanced diet and long-term health problems.
Weight Gain: Consuming high-fat and high-sugar foods can cause weight gain, especially if portion
sizes are not controlled.
Blood Sugar Imbalance: High sugar content in fast food can lead to spikes in blood sugar levels,
which can be harmful for individuals with diabetes or other blood sugar issues.
Decreased Energy: Consuming high-fat and high-sugar foods can lead to decreased energy levels and
a decrease in physical performance.
6.
When you order Health food…vendors
vs Age of respondent (Q6 vs Q7): The chi
square result indicates that the verification of content added as per claims made by vendors is
dependent on the age of the respondent. The graph shows that the highest percentages of checks
correspond to respondents up to 40 years of age. -22% never check the content as per claims made by
vendors.
-78% sometimes or always check the content as per claims made by vendors, 70% are aged 40 years
or younger.
7.
Q8 vs Q7: The chi square result indicates that respondents feel that they are consuming more
food every week by including online food according to their age. The graph shows that the highest
percentages of increase in consumption correspond to respondents up to 40 years of age
-52% feel that consumption is increasing. 49% of those who feel that consumption is increasing are
40 years old or younger. 5% of this age group feel that consumption is the same.
- 35% feel that consumption is not increasing. 29% of those who feel that consumption is not
increasing are 40 years of age or less. The widespread practice of online food ordering can lead to
several potential risks associated with consuming more food, including:
Increased portion sizes: Online food ordering often makes it easy to order larger portion sizes than
what you would normally eat, which can lead to overconsumption and weight gain.
Convenient unhealthy options: Online food ordering platforms often have a wider selection of
unhealthy food options, such as high-fat and high-sugar foods, which can be more tempting and
easier to order than healthier options.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Lack of self-control: When ordering food online, customers do not have the opportunity to see or
smell the food before they eat it, which can make it easier to overeat or make unhealthy choices.
Inaccurate nutrition information: The nutritional information provided online may not always be
accurate, which can lead to incorrect information about the food being consumed.
Emotional eating: Online food ordering can make it easier to indulge in emotional eating, as
customers may order food for comfort or as a reward, rather than for sustenance.
It is important to be mindful of portion sizes and to make informed choices about what you are eating,
whether ordering food online or not. Practicing self-control, being aware of your food choices, and
being mindful of portion sizes can help mitigate the risks associated with overconsumption.
8. Do you feel that ordering food via online platforms…people vs Age of Respondent (Q9 vs Q7):
The chi square result shows that feel that ordering food online platforms has a distinct advantage is
dependent on the age of the respondents. The graph shows that the majority of those who feel it has a
distinct advantage are under the age of 40 years old.
-63% consider that ordering food online platforms has a distinct advantage, 53% are under 40 years of
age.
- 37% consider that ordering food online platforms do not has a clear advantage.
The table 8 shows the results of the relationship between the respondents' age (Q7) and their
perception of the advantage of ordering food online (Q9). The following inferences can be drawn
from the results:
Younger generations prefer online ordering: The majority of the respondents under 30 years old (76
out of 108, or approximately 70%) felt that ordering food online has a distinct advantage.
Older generations less likely to see advantage: The majority of respondents over 30 years old (51 out
of 179, or approximately 29%) felt that ordering food online does not have a distinct advantage.
Age as a factor in online ordering preferences: The results suggest that age may be a factor in
determining a person's perception of the advantage of ordering food online, with younger generations
being more likely to see it as an advantage.
Increased adoption of online ordering: The results also suggest that the adoption of online ordering
for food is increasing, as a majority of the respondents (181 out of 287, or approximately 63%) felt
that it has a distinct advantage.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
9. Does your over all food bills increase due to online ordering vs Age of respondent (Q10 vs Q7):
The chi square result shows that the overall food bill increases due to on line ordering is age
dependent. The graph shows that the majority indicate that it has not increased.
-44% percent believe that the overall food bill has not increased, 41% are aged 40 years or less. 16% feel that the overall food bill has increased moderately or significantly, 11% are aged 40 years
or younger.
-18% have not tried to verify increase.
16 percent or nearly 44 out of 287 respondents feel that their overall food bill has increased
moderately or significantly. It is important for such people to regularly review your spending and to
make informed decisions about food ordering to ensure that it is a financially sustainable choice.
Consider options such as home cooking, reducing portion sizes, or opting for less expensive food
options to minimize the impact of increased food costs.
10.How many times do you order food using online platforms vs Do you order fast food? (Q1 vs Q2):
The chi square result shows that ordering fast food is dependent on the number of times food is
ordered using the platform. The graph shows that respondents mostly order fast food always or
sometimes when they use platforms up to 15 times per month.
-84% always or sometimes order fast food: 73% order fast food when they use the platform up to 15
times a month.
- 16% never order fast food. 10% never order when they use the platform up to 15 times a month.
Studying the relationship between online food ordering and fast-food consumption can provide
valuable insights into consumer behaviour, health, marketing, nutrition, and economics, which can
inform policy and decision-making in these areas. By studying the relationship between the
frequency of ordering food online and fast-food consumption, researchers can assess the potential
impact on public health and the health implications of frequent fast-food consumption. Nutritional
awareness: By studying the relationship between online food ordering and fast-food consumption,
researchers can assess the level of nutritional awareness among consumers and the extent to which
this impacts their food choices.
11.How many times do you order food using online platforms vs Do you order Health food? (Q1 vs
Q3): The chi square result shows that ordering health food is dependent on the number of times food
is ordered using the platform. The graph shows that respondents order health food only or majority of
time sometimes when they use up to 15 times per month platforms.
-62% only or majority of time order health food. 55% order health food when they use the platform
up to 15 times a month.
- 13% never order health food. 10% never order when using the platform up to 15 times a month.
12. Do you order fast food vs Have you visited the restaurants from where you order food online to
ascertain cleanliness of the kitchen and the staff (Q2 vs Q4): Chi square test shows that visits to
online food restaurants in order to check the cleanliness of the kitchen and staff depend on ordering
fast food. The graph shows that most visits are made when ordering fast food sometimes or always.
-52% who order fast food sometimes or always visit the restaurants.
- 32% who order fast food sometimes or always do not visit the restaurants. 16% never order fast food.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
13. Do you order Health Food vs Have you visited the restaurants from where you order food online
to ascertain cleanliness of the kitchen and the staff? (Q3 vs Q4): Chi square result test shows that
visits to the restaurants of food online in order to ascertain cleanliness of the kitchen and the staff is
dependent on ordering health food. The graph shows that most visits are made when ordering mostly
or only health food.
-37% percent who order only or mostly health food always visit the restaurants.
- 26% who order only or mostly health food do not visit the restaurants.
- 5% who never order fast food, do visit restaurants.
- 13% never order fast food.
It is always recommended to take the necessary precautions when ordering food online and to
thoroughly research the restaurant and its food safety practices before placing an order.
14. Do you order fast food vs Do you order Health Food? (Q3 vs Q2): The chi square result shows
that ordering health food and fast food are not independent. The graph shows that the respondents
order sometime and always fast food considering that they only or mostly order health food.
-40% order health food and consider that they always or sometimes order fast food.
- 14% consider that they always order health food and always fast food.
-7% do not order fast food or health food.
Popularity of health food: The majority of the respondents (60 out of 287, or approximately 21%)
reported ordering health food a majority of times.
Preference for fast food: The majority of the respondents (178 out of 287, or approximately 62%)
reported ordering fast food sometimes, while 39 respondents (approximately 14%) always ordered
fast food.
Combined fast food and health food consumption: 76 respondents (approximately 26%) reported
ordering both fast food and health food sometimes.
Limited consumption of health food: 70 respondents (approximately 24%) reported ordering health
food on a few occasions, while only 4 respondents (approximately 1%) never ordered health food.
Rare consumption of only health food: Only 12 respondents (approximately 4%) reported only
ordering health food.
15. How many times do you order food using online platforms vs Have you visited the restaurants
from where you order food online to ascertain cleanliness of the kitchen and the staff (Q1 vs Q4) The
chi square result indicates that visits to restaurants is independent of the frequency of use of the
platform. - 16% of participants who order between 3 to 30 times per month do not visit restaurants
For questions 4.12,13 and 15 there is a sizeable percentage of respondents who do not visit the
restaurants to ascertain the cleanliness of the restaurant or the staff. The risks of doing so are listed
below.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Food Safety: Without being able to see the kitchen and observe food preparation practices, there is no
way to guarantee that the food is being handled and prepared in a clean and sanitary manner. This can
increase the risk of foodborne illness.
Allergens: If you have food allergies or sensitivities, it can be difficult to communicate those needs
when ordering food online. There is a risk of cross-contamination or incorrect information being
provided, which can result in serious health consequences.
Hygiene: The hygiene standards of the delivery person may also be a concern, as they are handling
the food during transport.
1- Q1 vs Q7
Q1 (How many times do you order food using platforms?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Less than
three
times a
month
Between 3
and 7 times
a month
Between 8
and 15
times a
month
Between 15
and 30
times a
month
Between 30
and 50
times a
month
More
than 50
times a
month
30
37
23
6
11
1
108
13
31
37
4
1
0
86
4
16
14
6
2
1
43
3
9
9
2
2
2
27
1
3
2
0
0
0
6
2
3
0
0
0
0
5
Others Total
0
9
2
0
0
1
12
53
108
87
18
16
5
287
The above table shows the frequency of how many times people order food using online platforms,
broken down by age group. The rows show the different age groups, while the columns show the
different frequency ranges in which people order food. For example, in the age group of 20 to 30
years old, 37 people order food less than three times a month, 31 people order food between 3 and 7
times a month, 16 people order food between 8 and 15 times a month, 9 people order food between
15 and 30
times a month, 3 people order food between 30 and 50 times a month, and 3 people order food more
than 50 times a month. Additionally, 9 people fall into the "others" category. Overall, the most
common frequency range for ordering food using online platforms is between 3 and 7 times a month,
and the majority of people fall into the age group of 20 to 30 years old. The same table is presented
as percentage in the table below.
Insights into Online Food Ordering: A Comprehensive Analysis of Qualitative and
Statistical Survey Results
Percentage table
Q1 (How many times do you order food using platforms?)
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Square chi Q1 (How many times do you order food using platforms?)
Less
than
three
times a
month
Between
3 and 7
times a
month
Between
8 and 15
times a
month
Between
15 and
30 times
a month
Between
30 and
50 times
a month
More
than
50
times
a
month
5.07
0.33
2.90
0.09
4.12
0.41
12.91
0.52
0.06
4.58
0.36
3.00
1.50
10.02
1.96
0.00
0.07
4.05
0.07
0.08
6.22
0.79
0.13
0.08
0.06
0.16
4.97
6.20
0.01
0.24
0.02
0.38
0.33
0.10
1.09
1.26
0.66
1.52
0.31
0.28
0.09
4.12
Others
Total
2.22
4.45
0.74
0.75
0.67
2.99
11.82
Square Chi
11.82
5.88
9.90
5.99
8.63
10.15
52.38
52.38
Q1 is not independent of Q7. The table immediately above is a chi-square test result for the
relationship between the frequency of ordering food using online platforms (Q1) and age
group (Q7). The values in the table represent the chi-square statistic for each cell, which
measures how much that cell's observed frequencies differ from the expected frequencies if
Q1 and Q7 were independent. The total chi-square value for the table is 52.38, which is
greater than the critical chi-square value for a 95% confidence level with 24 degrees of
freedom (which is 43.78). Therefore, we can reject the null hypothesis that Q1 and Q7 are
independent and conclude that there is a significant relationship between the two variables.
The table shows that there are some cells with higher chi-square values, indicating that the
differences between observed and expected frequencies are more pronounced in those cells.
For example, the cell for "Less than 20 years old" and "Less than three times a month" has a
chi-square value of 5.07, which suggests that there is a stronger relationship between these
variables than in other cells. Looking at the table, we can see that the highest frequency of
online food ordering is among individuals between the ages of 20 and 30, followed by those
between the ages of 30 and 40. The lowest frequency of online food ordering is among those
over 60 years old. This suggests that younger people are more likely to order food using
online platforms than older people. The relationship between age and frequency of online
food ordering could be due to a number of factors. Younger people may be more likely to use
technology and be comfortable with online ordering platforms. Additionally, younger people
may be more likely to live in urban areas, where online food ordering is more common and
accessible. Overall, these findings could have implications for the food industry and for online
ordering platforms. Companies may want to target younger customers in their marketing and
advertising, and also consider developing new features that are particularly appealing to
younger people. Conversely, companies may need to take steps to make their platforms more
accessible and user-friendly for older customers who may be less familiar with technology.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
1- Q2 vs Q7
Q2 (Do you order fast food?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Yes
Sometimes
31
66
62
9
9
1
178
Never
3
14
10
7
8
3
45
Alway
s
19
28
15
2
0
0
64
Total
53
108
87
18
17
4
287
The above table shows the count of individuals who order fast food categorized by age
groups. The data is cross-tabulated with the frequency of fast-food ordering, which is
classified as 'Yes, sometimes', 'Never', and 'Always'. We can observe that the majority of
individuals in all age groups order fast food, with the highest count in the age group of 2030, where 66 individuals order fast food sometimes, 14 individuals never order, and 28
individuals always order fast food. Looking at the data, it seems that as age increases, the
frequency of ordering fast food decreases. For example, in the age group of 40-50, only 2
individuals always order fast food, compared to 15 individuals who sometimes order and 7
individuals who never order. Similarly, in the age group of 50-60, none of the individuals
always order fast food.
Percentage table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Q2 (Do you order fast food?)
Yes Sometimes Never Always
11
1
7
23
5
10
22
3
5
3
2
1
3
3
0
0
1
0
62
16
22
Total
18
38
30
6
6
1
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi
Q7 (age)
square chi Q2 (Do you order fast food?)
Yes Sometimes
Never
Always
Total
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
0.11
0.01
1.20
0.42
0.23
3.39
0.51
0.97
6.18
10.68
4.36
0.64
1.00
1.01
3.79
7.86
1.16
3.17
7.61
14.69
above 60
Total
0.88
2.85
8.98
30.71
0.89
11.69
Square chi
10.75
45.25
45.25
lg column= 2 lg file= 5 total lg=10 Square chi > Square chi
95%=18.31 Ho is rejected. Q2 is not independent of Q7.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The above table presents the results of a survey asking respondents about their fast-food
ordering habits (Q2) and their age group (Q7). The table includes the counts of respondents
who answered "Yes," "Sometimes," "Never," and "Always" for Q2, broken down by age
group. The "Square chi" column presents the results of a chi-squared test, which is a statistical
test used to determine whether two variables are independent. The values in this column
represent the calculated chi-squared statistic for each age group. The "Total" row provides the
total count of respondents in each Q2 category. The final row, "Square chi" shows the overall
chi-squared statistic for the entire dataset. In this case, the overall chi-squared value is 45.25.
The interpretation of the chi-squared test suggests that there is a significant relationship
between fast food ordering habits (Q2) and age group (Q7). The null hypothesis (Ho) is
rejected as the calculated chi-squared value (45.25) is greater than the critical value of 18.31
(for 5 degrees of freedom, at a 95% confidence level). Therefore, it can be concluded that Q2
is not independent of Q7, and there is a significant relationship between age group and fastfood ordering habits among the survey respondents. The outcome that Q2 is not independent
of Q7, and that there is a significant relationship between age group and fast-food ordering
habits among the survey respondents, has several implications. Firstly, the results suggest that
age is a significant factor in determining whether a person orders fast food or not. This implies
that fast food companies should tailor their marketing and product offerings to different age
groups to maximize their sales. Secondly, the results may be useful for policymakers and
public health officials in developing interventions to promote healthier eating habits,
particularly among younger age groups. For example, campaigns aimed at reducing fast food
consumption could be targeted towards younger people who are more likely to order fast food.
Finally, the results may also be relevant for researchers interested in exploring the factors that
influence fast food consumption. The findings could be used to inform further studies that
investigate the relationship between age and other demographic factors, as well as other
lifestyle and health-related variables, in shaping fast food consumption patterns.
Q3 vs Q7
Q3 (Do you order health food?)
Count table
Q7 (age)
I only order
Health Food
I order Health
Food a majority
of times
I order Health
food on a few
occasions
I never
order
Health
food
Total
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
25
39
50
4
1
0
119
8
31
9
8
3
1
60
19
24
16
5
6
0
70
1
14
12
1
7
3
38
53
108
87
18
17
4
287
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The above table presents the results of a survey asking respondents about their health food
ordering habits (Q3), broken down by age group (Q7). The table includes the counts of
respondents who answered "I only order Health Food," "I order Health Food a majority of
times," "I order Health food on a few occasions," and "I never order Health food" for Q3,
broken down by age group.
The total number of respondents is 287. The total count of respondents in each category is
presented in the "Total" row and column.
The table shows that a majority of respondents (119) reported that they only order health food.
However, a significant number of respondents (38) reported that they never order health food.
The number of respondents who order health food a majority of the time or on a few occasions
are smaller in number.
The table also shows that there are age differences in health food ordering habits. For example,
the proportion of respondents who only order health food is highest among those aged 30-40
(50 out of 87), whereas the proportion of respondents who never order health food is highest
among those aged 20-30 (14 out of 108).
Overall, the table suggests that health food ordering habits are not uniform across different age
groups. It may be useful for food companies and public health officials to consider these
differences when developing strategies to promote healthy eating habits among different age
groups. Additionally, these results could be used to guide future research that investigates the
factors that influence health food ordering habits.
Percentage table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Q3 (Do you order health food?)
I only
order
Health
Food
9
14
17
1
0
0
41
I order
Health Food
a majority of
times
3
11
3
3
1
0
21
I order Health
food on a few
occasions
7
8
6
2
2
0
24
I never
order
Health
food
0
5
4
0
2
1
13
Total
18
38
30
6
6
1
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Square chi Q3 (Do you order health food?)
I order Health
I only order
Food a majority
Health Food
of times
0.42
0.75
5.38
1.61
5.19
1.66
15.00
0.86
3.14
4.64
4.77
0.09
0.03
13.53
I order Health
food on a few
occasions
2.85
0.21
1.28
0.08
0.83
0.98
6.23
lg column= 3 lg file= 5 total lg=15 Square chi > Square chi 95%=25.00
Ho is rejected. Q3 is not independent of Q7
I never
order
Health
food
5.16
0.01
0.02
0.80
10.02
11.52
27.53
Square chi
Total
9.29
4.10
11.32
7.27
16.13
14.19
62.29
62.29
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The above table presents the results of a chi-square test, testing the independence of health
food ordering habits (Q3) and age group (Q7) among the survey respondents. The observed
frequencies for each combination of Q3 and Q7 are presented in the table, along with the
expected frequencies based on independence. The chi-square statistic for the test is
presented in the last row and column. The results of the chi-square test suggest that health
food ordering habits and age group are not independent among the survey respondents. The
chi-square statistic of 62.29 is greater than the critical value of 25.00 at the 95% level of
confidence, indicating that the null hypothesis of independence should be rejected. This
suggests that there is a significant relationship between age group and health food ordering
habits among the survey respondents. In other words, the results suggest that the frequency
of health food ordering habits varies significantly across different age groups. It may be
useful to further investigate the factors that influence health food ordering habits among
different age groups, in order to develop targeted interventions aimed at promoting healthy
eating habits. 13% of respondents never order health food, 87% order health food
occasionally or more frequently. 56% order only or mostly health food and are under 40
years of age. Those older than 40 years order only or mostly in 6% of cases.
1- Q4 vs Q7
Q4 (Have you visited restaurants from you order….
cleanliness ..?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
No
23
48
26
9
Yes
30
60
61
9
Total
9
8
17
1
116
3
171
4
287
53
108
87
18
The above table shows the frequency distribution of survey respondents based on their response
to the question "Have you visited restaurants from where you order food and assessed the
cleanliness of the restaurant?" (Q4) and age group (Q7). The table shows that out of the 287
respondents, 171 respondents answered "Yes" to the question, while 116 respondents answered
"No". In terms of age group, the largest group of respondents was those between 20 and 30
years old, accounting for 108 of the respondents. Based on the data, we can see that a majority
of respondents have visited restaurants and assessed their cleanliness. Additionally, we can see
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
that there are differences in the distribution of respondents across age groups. The results of
this table can be useful for restaurant owners or managers who want to improve the cleanliness
of their establishment. By knowing that a significant number of their customers have assessed
the cleanliness of their restaurant, they can focus on improving cleanliness and sanitation
practices to retain their customers and attract new ones.
Percentage table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Q4 (Have you visited restaurants from you order cleanliness ..?)
No
8
17
9
3
3
0
40
Yes
10
21
21
3
3
1
60
Total
18
38
30
6
6
1
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
Square chi Q4 (Have you visited restaurants from you order...cleanliness?)
No
0.12
0.43
2.39
0.41
0.66
0.24
4.24
Yes
0.08
0.29
1.62
0.28
0.45
0.16
2.88
Square chi
Total
0.20
0.73
4.01
0.69
1.11
0.39
7.12
7.12
The above table represents the results of a chi-squared test, which is used to determine if there
is a statistically significant relationship between two categorical variables. In this case, the
variables being analysed are the response to question 4 ("Have you visited the restaurants from
where you order food online to ascertain cleanliness of the kitchen and the staff?") and age
group (question 7).
The table shows the observed frequencies of each combination of responses to question 4 and
age group, as well as the total observed frequencies for each age group and for the entire sample.
The "Square chi" column shows the contribution of each cell to the overall chi-squared statistic,
which is calculated by summing the squared differences between the observed and expected
frequencies across all cells.
The total chi-squared value is 7.12, which indicates that there is a significant relationship
between the two variables (assuming a significance level of 0.05). This means that the
likelihood of someone visiting a restaurant to check cleanliness and staff behaviour is not
independent of their age group. For example, the table shows that people between the
ages of 30 and 40 are more likely to check cleanliness and staff behaviour compared to
those in other age groups. On the other hand, people under 20 and over 60 are less likely
to check these factors. This information can be useful for restaurants and food delivery
services to target specific age groups with their marketing campaigns and improve their
services to meet the needs of their target audience. The result of chi square indicates that
visits to restaurants are independent of the age of the respondents. Visits to restaurants
turned out to be independent of age. 60% visit the restaurants from where they order food
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
online in order to ascertain of the kitchen and the staff. 42% are aged between 20 to 40
years old.
Q5 vs Q7
Q5 (When you order fast food do you
check
… fat and
sugar
content?)
Count table
Always
Less than 20 years old
13
33
Sometimes when
it Is declared in
the
menu
7
Between 20 and 30 old
26
57
25
108
Between 30 and 40 old
22
53
12
87
Between 40 and 50 old
4
10
4
18
Between 50 and
60 years old
9
2
6
17
above 60
Total
2
76
2
157
0
54
4
287
Q7 (age)
Never
Total
53
The above table shows the counts of survey respondents in different age groups based on
their responses to the question "When you order fast food, do you check the fat and sugar
content?" The respondents were able to choose from three options: "Never," "Always," and
"Sometimes when it is declared in the menu." There are 287 total respondents in the survey.
Among them, 76 said they never check the fat and sugar content of fast food they order, 157
said they always check, and 54 said they sometimes check when it is declared in the menu.
Looking at the different age groups, the majority of respondents in each group said they
always check the fat and sugar content of fast food, with the highest percentage in the 20-30
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
age group at 52.8%. The 50-60 age group had the highest percentage of respondents who
never check at 52.9%.
Overall, the table suggests that a significant portion of survey respondents prioritize checking
the fat and sugar content of fast food when they order. However, there are also a sizeable
number of respondents who do not check, particularly in the older age groups. The outcome
suggests that while a significant number of respondents do check the fat and sugar content when
ordering fast food, a considerable proportion of them do not, especially in the older age groups.
This could indicate that there is a need for more education and awareness campaigns to
encourage healthier eating habits, particularly among older adults. It could also indicate that
there is a need for more accessible information about the nutritional content of fast food, such
as clearer labelling and more transparency from fast food establishments. Overall, this
information could be useful for policymakers and public health advocates who seek to improve
the dietary habits of the general population.
Q5 (When you order fast food do you check Percentage table … fat
and sugar content?)
Sometimes when it Total
Always Is declared in
Q7
Neve
the
s
(age)
r
menu
Less than 20 years old
5
11
2
18
9
20
9
38
Between 20 and 30 old
8
18
4
30
Between 30 and 40 old
1
3
1
6
Between 40 and 50 old
3
1
2
6
Between 50 and 60 years old
above 60
1
1
0
1
Total
26
55
19
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi Q5 (When you order fast food do you check … fat and sugar content?)
Sometimes when it
Is declared in
Q7 (age)
Never
Always
the
menu
Less than 20 years old
0.08
0.55
0.89
0.24
0.07
1.08
Between 20 and 30 old
0.05
0.61
1.17
Between 30 and 40 old
0.12
0.00
0.11
Between 40 and 50 old
4.49
5.73
2.45
Between 50 and 60 years old
Total
1.52
1.39
1.83
0.24
12.68
above 60
0.84
0.02
0.75
1.60
Total
5.81
6.99
6.45
19.25
Square chi
19.25
lg column= 2 lg file= 5 total lg=10 Square chi > Square chi 95%=18.31
The values of square chi and square chi95% are close, so there is not enough statistical
evidence to conclude that Q5 is not independent of Q7. The square chi test shows that there
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
is not enough statistical evidence to conclude that there is a significant relationship between
age group and the frequency of checking fat and sugar content in fast food orders. The
values of square chi and square chi95% are close, which means that we cannot reject the
null hypothesis that the two variables are independent. However, we can observe that the
older age groups have a higher proportion of respondents who never check the fat and sugar
content, while the younger age groups have a higher proportion of respondents who always
or sometimes check. This information can be useful for fast food companies to target their
marketing and nutrition education campaigns to different age groups. One non-marketing
implication of this outcome could be that there may be a need for more education and
awareness about healthy eating habits for older adults, who are less likely to check the
nutritional content of fast food. This could include public health campaigns, nutrition
education programs, or other initiatives aimed at increasing knowledge and awareness about
the importance of healthy eating habits, especially among the elderly population.
The chi square result indicates that there is insufficient statistical evidence to ensure that
the percentage of fat and sugar check is age-dependent. The graph shows that the highest
percentages of checking correspond to respondents up to 40 years of age. 74% sometimes
or always check the percentage of fat and sugar when they order fast food. 42% are under
40 years of age. 26% never check fat and sugar percentages.
Q6 vs Q7
Q6 (When you order health food do you verify contents
to make as per claims ?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
Neve
r
14
17
14
6
10
2
63
Always
Total
29
64
63
9
Sometime
s
10
27
10
3
6
1
17
1
1
4
172
52
287
53
108
87
18
The table shows the count of respondents in different age groups who answered questions
about verifying the contents of health food when ordering from vendors. The responses are
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
categorized as "Never," "Always," and "Sometimes." For example, in the age group of 20-30
years old, out of the 108 respondents, 17 said they never verify, 64 said they always verify,
and 27 said they sometimes verify. The total count for each response category across all age
groups is shown in the last row of the table. Out of the 287 respondents, 63 never verify, 172
always verify, and 52 sometimes verify. The table provides information about the frequency
of verifying the contents of health food when ordering from vendors, but it does not provide
information about the reasons why respondents choose to verify or not verify the contents.
One implication of this outcome is that a majority of the survey respondents (60%) report that
they always verify the contents of health food when they order it. This suggests that there is a
significant level of awareness and concern among consumers about the health claims made by
food vendors, and a desire to ensure that the food they are eating is actually healthy. On the
other hand, a non-negligible proportion of respondents (22%) reported that they never or only
sometimes verify the contents of health food, indicating a potential lack of understanding or
awareness about healthy eating and food labelling.
Q6 (When you order health food do you verify contents to
Percentage table make as per claims?)
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
Neve
r
5
6
5
2
Always
Sometime
Total
10
22
22
3
3
9
3
1
18
38
30
6
3
2
0
6
1
0
0
18
1
100
22
60
s
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
Square chi Q6 (When you order health food do you verify contents to
make as per claims?)
Never
0.48
1.90
1.36
1.06
Always
0.24
0.01
2.26
0.30
Sometimes
0.02
2.82
2.11
0.02
Total
10.53
1.72
1.40
13.66
1.43
16.76
0.81
5.34
0.10
6.48
Square chi
lg column= 2 lg file= 5 total lg=10 Square chi > Square chi 95%=18.31
Ho is rejected. Q6 is not independent of Q7
0.74
4.73
5.73
1.38
2.35
28.58
28.58
The square chi analysis shows that the value of square chi is greater than the square chi
95%, indicating that there is sufficient statistical evidence to reject the null hypothesis
(Ho) that Q6 is independent of Q7. This implies that there is a relationship between age
group and the frequency of verifying health food contents as per the claims made by
vendors. The table also shows that respondents in the older age groups (above 50 years)
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
are less likely to verify health food contents compared to the younger age groups, while
the younger age groups are more likely to always or sometimes verify health food
contents. This could suggest that the older age groups may be less health-conscious or
less concerned about the accuracy of the claims made by vendors, while the younger age
groups may be more health-conscious and attentive to the accuracy of the claims made
by vendors. One potential risk or implication of the finding that older respondents are
less likely to verify health food contents is that they may be more vulnerable to health
risks associated with consuming mislabelled or adulterated food. As people age, they
may become more susceptible to certain health conditions, and it is possible that
consuming foods that are not accurately labelled could exacerbate these conditions.
Additionally, older adults may be more likely to have compromised immune systems,
which could make them more susceptible to foodborne illness or other negative health
effects from consuming contaminated or mislabelled food. Therefore, if older adults are
not verifying health food contents, they may be putting themselves at greater risk of
health problems. The chi square result indicates that the verification of content added as
per claims made by vendors is dependent on the age of the respondent. The graph shows
that the highest percentages of checks correspond to respondents up to 40 years of age.
22% never check the content as per claims made by vendors. 78% sometimes or always
check the content as per claims made by vendors, 70% are aged 40 years or younger.
Q8 vs Q7
Q8 (Do you think that you are consuming more every week
online food?)
Count table
Q7 (age)
Yes
No
Total
intake
remains
the same
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60
years old
above 60
Total
37
67
36
5
11
30
43
7
4
7
6
5
1
4
2
1
53
108
87
18
4
8
4
1
17
1
150
1
100
1
27
1
10
4
287
Not Sure
Total
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Percentage table
Q8 (Do you think that you are consuming more every week online food?)
Looking at the data, we can see that out of the total 287 respondents, 150 or 52% answered
"Yes," indicating that they believe they are consuming more food every week by including
online food. Meanwhile, 100 or 35% respondents answered "No," indicating that they do not
think they are consuming more food every week by including online food. 27 or 9%
respondents said that their total intake remained the same, while 10 or 4% were not sure.
Breaking the data down by age group, the highest number of "Yes" responses was from the
age group between 20 and 30 years old, with 67 out of 108 respondents (62%) in this age
group answering "Yes." Among those under 20 years old, 37 out of 53 respondents (70%)
answered "Yes." In contrast, the age group between 40 and 50 years old had the lowest
number of "Yes" responses, with only 5 out of 18 respondents (28%) answering "Yes." The
potential health risks and implications of the outcome that 52% of the respondents believe they
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
are consuming more food every week by including online food can vary depending on the
individual's dietary habits and lifestyle.
Firstly, consuming more food than what is necessary can lead to weight gain, obesity, and
related health problems such as high blood pressure, type 2 diabetes, heart disease, and stroke.
Overconsumption of certain food items, such as those high in sugar, salt, and saturated fat, can
further increase the risk of these health problems. Secondly, online food ordering can make it
easier for people to choose less healthy options, such as fast food, which tend to be high in
calories and low in nutrients. If individuals rely on online food ordering for most of their
meals, they may not be getting enough essential nutrients, such as fibre, vitamins, and
minerals, that are important for maintaining good health. Thirdly, a sedentary lifestyle is also
associated with negative health outcomes, including obesity and chronic disease. Online food
ordering can encourage a more sedentary lifestyle if individuals are not actively engaged in
preparing meals or going out to purchase food. In summary, if individuals believe they are
consuming more food every week by including online food, it is important for them to be
mindful of their food choices, portion sizes, and physical activity levels to prevent negative
health outcomes.
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
Square chi Q8 (Do you think that you are consuming
more every week online food?)
Yes
No
Total
intake
remains
the same
3.12
1.97
1.97
2.07
3.02
1.55
5.31
0.08
0.20
0.98
0.58
6.46
0.39
0.01
0.35
0.22
6.72
4.52
8.22
8.83
2.69
0.73
3.60
0.28
7.30
0.57
12.39
0.11
10.80
1.03
12.86
Not Sure
Total
5.31
6.57
Square
chi
lg column= 3 lg file= 5 total lg=15 Square chi > Square chi 95%=25.00
Ho is rejected. Q8 is not independent of Q7
7.03
42.61
42.61
The finding of a statistically significant relationship between age and the effect of online food
on food consumption suggests that age may be an important factor to consider when analysing
the impact of online food on diet and health. For example, health professionals and
policymakers who are concerned about the potential health consequences of online food
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
consumption may want to tailor their messages and interventions to different age groups based
on their likelihood to consume more food when ordering online. This could include developing
targeted health promotion campaigns or educational materials that address the specific
concerns or challenges faced by different age groups.
Similarly, food delivery platforms and restaurants may want to consider the potential impact
of their services on different age groups and develop strategies to promote healthier food
choices or portion sizes to those who may be more susceptible to overconsumption. Overall,
the finding of a significant relationship between age and the effect of online food on food
consumption underscores the importance of considering age as a key factor when designing
and implementing interventions to promote healthy eating and prevent overconsumption. The
chi square result indicates that respondents feel that they are consuming more food every week
by including online food according to their age. The graph shows that the highest percentages
of increase in consumption correspond to respondents up to 40 years of age. 52% feel that
consumption is increasing. 49% of those who feel that consumption is increasing are 40 years
old or younger. 5% of this age group feel that consumption is the same. 35% feel that
consumption is not increasing. 29% of those who feel that consumption is not increasing are
40 years of age or less.
1- Q9 vs Q7
Q9 (Do you feel thar ordering food via online… has a
distinct advantage of not …...?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
No
14
32
51
7
Yes
39
76
36
11
Total
2
15
17
0
106
4
181
4
287
53
108
87
18
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Percentage table
Q9 (Do you feel thar ordering food via online
distinct advantage of not
has a
?)
Q7 (age )
No
Yes
Total
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
5
11
18
2
1
0
37
14
26
13
4
5
1
63
18
38
30
6
6
1
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi Q9 (Do you feel thar ordering food via online. Has a
distinct advantage of not …...?)
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
No
Yes
Total
1.59
1.56
11.08
0.02
2.92
1.48
18.64
0.93
0.91
6.49
0.01
1.71
0.87
10.92
Square chi
2.52
2.47
17.57
0.03
4.62
2.34
29.55
29.55
lg column= 1 lg file= 5 total lg=5 Square chi > Square chi 95%=11.07
Ho is rejected. Q9 is not independent of Q7
The chi square result shows that feel that ordering food online platforms has a distinct
advantage is dependent on the age of the respondents. The graph shows that the majority
of those who feel it has a distinct advantage are under the age of 40 years old. 63%
consider that ordering food online platforms has a distinct advantage, 53% are under 40
years of age. 37% consider that ordering food online platforms do not has a clear
advantage.
1- Q10 vs Q7
Q10 (Does your over all food bill increase due to online
ordering?)
Count table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60
years old
above 60
Total
No, it has
not
increased
Have not
made an
attempt to
verify
It has
increased by
a small
percentage
It has
increased
by a
moderate
percentage
It has
increased
significantly
Total
24
43
51
4
13
24
6
3
7
25
24
5
4
12
4
6
5
4
2
0
53
108
87
18
3
4
5
4
1
17
1
126
1
51
0
66
1
31
1
13
4
287
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Based on the above table, it appears that a majority of respondents in all age groups reported
that their overall food bill has increased due to online ordering, with 66 respondents (23%)
reporting a small increase, 31 (11%) reporting a moderate increase, and 13 (5%) reporting a
significant increase. When looking at specific age groups, the table suggests that respondents
in the age group of 20-30 years old reported the highest number of moderate and significant
increases, while those in the age group of 4050 years old reported the lowest number of
increases overall. Overall, the data in this table suggests that online ordering has increased the
overall food bill for a significant proportion of respondents across different age groups. This
finding could have implications for both consumers and food businesses, as it suggests that
online ordering may not always lead to cost savings and that consumers may need to be more
mindful of their spending when ordering food online. For food businesses, this finding
suggests that they may need to consider strategies to help consumers manage their spending
or offer pricing models that are more transparent and cost-effective.
Percentage table
Q10 (Does your over all food bill increase due to online
ordering?)
Q7 (age)
No, it has
not
increased
Have not
made an
attempt
to verify
It has
increased by
a small
percentage
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years old
above 60
Total
8
15
18
1
1
0
44
5
8
2
1
1
0
18
2
9
8
2
2
0
23
It has
increased
It has
by a
increased
moderate significantly
percentage
1
4
1
2
1
0
11
2
1
1
0
0
0
5
Total
18
38
30
6
6
1
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q7 (age)
Less than 20 years old
Between 20 and 30 old
Between 30 and 40 old
Between 40 and 50 old
Between 50 and 60 years
old
above 60
Total
Square chi Q10 (Does your over all food bill increase due to
online ordering?)
No, it has not
increased
Have not
made an
attempt to
verify
It has
increased by a
small
percentage
It has
increased
by a
moderate
percentag
e
It has
increased
significantly
Total
0.02
0.41
4.29
1.93
1.36
1.20
5.79
0.01
2.21
0.00
0.80
0.18
0.52
0.01
3.10
8.46
2.81
0.16
0.96
0.82
6.93
1.79
14.93
11.39
2.67
0.32
0.30
2.55
0.07
5.91
0.33
9.65
0.12
8.80
0.92
4.41
0.75
15.39
3.70
8.52
Square chi
5.81
46.76
46.76
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
lg column= 4 lg file= 5 total lg=20 Square chi > Square chi 95%=31.42
Ho is rejected. Q10 is not independent of Q7
The table indicates that the chi-square statistic is 46.76, which is greater than the critical value
of 31.42 at the 95% confidence level with 16 degrees of freedom. This suggests that the null
hypothesis (Ho) of independence between Q7 and Q10 should be rejected, and that there is a
statistically significant relationship between the two variables. The table also shows that the
highest chi-square values are observed for the response categories "It has increased by a
moderate percentage" and "It has increased significantly", indicating that these response
categories are driving the relationship between the two variables. This suggests that the effect
of online ordering on the overall food bill may vary by age group, and that younger age groups
may be more likely to report a moderate or significant increase in their food bill due to online
ordering. In conclusion, the data in this table indicates that there is a significant relationship
between age and the effect of online ordering on the overall food bill, and that younger age
groups may be more likely to report an increase in their food bill due to online ordering. This
finding could have implications for both consumers and food businesses, as it suggests that
online ordering may have different effects on spending patterns across different age groups,
and that businesses may need to consider age-specific pricing or marketing strategies to
effectively target different age groups.
Another implication/concern for this outcome could be the financial burden on younger age groups. If
younger people are more likely to report an increase in their food bill due to online ordering, it may
suggest that they are more financially strained or have less control over their spending compared to
older age groups. This could have wider implications for their financial well-being and ability to
manage their expenses. The chi square result shows that the overall food bill increase due to on line
ordering is age dependent. The graph shows that the majority indicate that it has not increased.
44% percent believe that the overall food bill has not increased, 41% are aged 40 years or less.
16% feel that the overall food bill has increased moderately or significantly, 11% are aged 40
years or younger. 18% have not made an attempt to verify increase.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Q1 vs Q2
Q2 (Do you order fast food?)
Count table
Q1 (How many times do you
order
food
using
platforms?)
Less than three times a month
Between 3 and 7 times a month
Between 8 and 15 times a month
Yes
Sometimes
Always
Total
Neve r
62
19
27
108
64
3
19
86
32
6
5
43
13
7
7
27
4
0
2
6
1
2
178
1
9
45
3
1
64
5
12
287
Between 15 and 30 times a month
Between 30 and 50 times a month
More than 50 times a month
Others
Total
The above table shows the relationship between the frequency of ordering food using
platforms and whether the individual orders fast food or not. The rows represent the frequency
of food ordering and the columns represent the response to the question "Do you order fast
food?". The cells contain the count of individuals falling into each category. Looking at the
table, we can see that the majority of respondents who order food less than three times a
month also order fast food. As the frequency of food ordering increases, the number of
individuals who order fast food decreases. Among those who order food always, only 5%
order fast food, while the majority of them (67%) do not order fast food. The relationship
between Q1 and Q2 is not straightforward, but we can conclude that there is a negative
association between the frequency of food ordering and ordering fast food.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Q2 (Do you order fast food?)
Percentage table
Q1 (How many times do you order
food using platforms?)
Less than three times a month
Between 3 and 7 times a
month
Between 8 and 15 times a
month
Between 15 and 30 times a
month
Between 30 and 50 times a
month
More than 50 times a month
Others
Total
Yes Sometimes
Never
Always
Total
22
7
9
38
22
1
7
30
11
2
2
15
5
2
2
9
1
0
1
2
0
1
62
0
3
16
1
0
22
2
4
100
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q1 (How many times do you order food
using platforms?)
Less than three times a month
Between 3 and 7 times a month
Between 8 and 15 times a month
Between 15 and 30 times a
month
Between 30 and 50 times a
month
More than 50 times a month
Others
Total
Square chi Q2 (Do you order fast food?)
Yes Sometimes
Never
Always
Total
0.37
2.13
1.07
0.25
8.15
0.74
0.35
0.00
2.20
0.98
10.28
4.00
13.90
0.08
0.17
14.15
0.02
0.94
0.33
1.29
1.42
3.98
22.89
0.06
26.93
37.15
3.19
1.05
7.29
Square chi
4.67
31.96
67.33
67.33
lg column= 2 lg file= 6 total lg=12 Square chi > Square chi 95%=21.03
Ho is rejected. Q1 is not independent of Q2
The table shows the results of a chi-square test of independence conducted on the relationship
between Q1 (frequency of using food ordering platforms) and Q2 (ordering fast food). The
calculated value of the chi-square statistic (67.33) is greater than the critical value at the 95%
confidence level (21.03), indicating a significant association between the two variables.
The table indicates that respondents who order food using platforms more frequently are more
likely to also order fast food. For example, those who order food always (the highest
frequency category) are overwhelmingly more likely to also order fast food, with a square chi
value of 10.28 compared to the other categories. Conversely, those who order food less
frequently (less than three times a month) are less likely to order fast food, with a square chi
value of 0.37 compared to the other categories.
In conclusion, the data suggest that there is a relationship between the frequency of using food
ordering platforms and the tendency to order fast food, with more frequent platform users
being more likely to order fast food. This finding could have implications for marketing
strategies and platform design aimed at promoting healthier food choices. 84% always or
sometimes order fast food: 73% order fast food when they use the platform up to 15 times a
month. 16% never order fast food. 10% never order when they use the platform up to 15 times
a month.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Q1 vs Q3
Q3 (Do you order health food?)
Count table
Q1 (How many
times do you
order food using
platforms?)
Less than three
times a month
Between 3 and 7
times a month
Between 8 and 15
times a month
Between 15 and
30 times a
month
Between 30 and
50 times a
month
More than
50 times a
month
Others
Total
I only order
Health Food
I order
Health Food
a majority
of times
I order
Health food
on a few
occasions
I never
order
Health
food
48
18
23
19
108
47
21
13
5
86
16
9
15
3
43
7
9
10
1
27
0
1
5
0
6
0
2
2
1
5
1
119
0
60
2
70
9
38
12
287
Total
Looking at the table, it can be observed that the majority of the respondents (60) order health
food a majority of times, while 119 respondents only order health food. On the other hand, 38
respondents never order health food, and 70 respondents order health food on a few occasions.
The distribution of the respondents' preference for health food varies across the different
frequency categories of ordering food. For instance, in the category of ordering food less than
three times a month, the majority of the respondents (48) only order health food, while in the
category of ordering food between 8 and 15 times a month, the majority of the respondents
(15) order health food on a few occasions.
Here are some non-statistical inferences that can be drawn from the provided outcome:
There is a noticeable interest in health food among the respondents as over half of them (60)
reported ordering it a majority of times. A significant number of respondents (119) only order
health food, which indicates that there is a niche market for healthy food options.
The distribution of preference for health food varies across the different frequency categories
of ordering food, which implies that different people have different priorities when it comes to
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
their food choices. The fact that 38 respondents never order health food suggests that there is
still a sizeable portion of the population that may not be interested in healthy food options.
The data indicates that the frequency of ordering food is associated with the preference for
health food, with the highest proportion of respondents who only order health food being in
the category of ordering food less than three times a month. This suggests that people who
order food less frequently may be more likely to prioritize health in their food choices.
Percentage table
Q1 (How many
times do you order
food using
platforms?)
Between 3 and 7
times a month
Between 8 and 15
times a month
Between 15 and 30
times a month
Between 30 and 50
times a month
More than 50
times a month
Others
Total
Q3 (Do you order health food?)
17
I order
Health Food
a majority of
times
6
I order
Health food
on a few
occasions
8
I never
order
Health
food
7
16
7
5
2
30
6
3
5
1
15
2
3
3
0
9
0
0
2
0
2
0
1
1
0
2
0
41
0
21
1
24
3
13
4
100
I only order
Health Food
Total
38
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Q1 (How many times
do you order food
using platforms?)
Less than three
times a month
Between 3 and 7
times a month
Between 8 and 15
times a month
Between 15 and 30
times a month
Between 30 and 50
times a month
More than 50 times
a month
Others
Total
Square chi Q3 (Do you order health food?)
I only order
Health Food
I order
Health Food
a majority
of times
I order Health
food on a few
occasions
I never
order
Health
food
Total
0.23
0.93
0.42
1.55
3.13
3.61
0.51
3.03
3.58
10.73
0.19
0.00
10.75
1.27
12.21
2.06
1.99
1.94
0.09
6.09
2.49
0.05
8.55
0.79
11.88
2.07
0.87
0.50
0.17
3.62
3.18
13.83
2.51
6.86
0.29
25.49
34.57
42.03
Square
chi
40.55
88.21
lg column= 3 lg file= 6 total lg=18 Square chi > Square chi 95%=28.88
Ho is rejected. Q1 is not independent of Q3
88.21
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The calculated chi-square value is 88.21, which is larger than the critical value of 28.88 at the
95% level of significance. This suggests that we reject the null hypothesis that Q1 and Q3 are
independent, indicating that there is a significant association between the two variables.
Looking at the individual values in the table, we can see that the distribution of responses for
Q3 varies across the different categories of ordering frequency in Q1. For example, in the
category of ordering food less than three times a month, the majority of respondents (48) only
order health food. In contrast, in the category of ordering food between 8 and 15 times a month,
the majority of respondents (15) order health food on a few occasions.
Overall, this suggests that individuals' frequency of ordering food using platforms is associated
with their likelihood of ordering health food, with different ordering frequency categories
having different patterns of health food ordering. The chi square result shows that ordering
health food is dependent on the number of times food is ordered using the platform. The graph
shows that respondents order health food only or majority of time sometimes when they use
up to 15 times per month platforms. 62% only or majority of time order health food. 55% order
health food when they use the platform up to 15 times a month. 13% never order health food.
10% never order when using the platform up to 15 times a month.
1- Q2 vs Q4
Q2 (Do you order fast food?)
Count table
Q4 (Have you visited the
restaurants from where you order
food online in order to ascertain
cleanliness of the kitchen and the
staff?)
Yes Sometimes
Never
Always
Total
Yes
125
23
23
171
No
53
22
41
116
178
45
64
287
Total
The above table displays the results of a survey conducted on two questions related to fast
food. The first question, labelled as Q2, asks whether the respondents order fast food, and the
second question, labelled as Q4, asks whether the respondents have visited the restaurants from
where they order food online in order to ascertain cleanliness of the kitchen and the staff. The
table is a count table that shows the number of respondents in each category for both questions.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The rows represent the responses to Q2, with "Yes", "Sometimes", and "Never" as the response
options. The columns represent the responses to Q4, with "Yes", "Sometimes", and "Never"
as the response options again. For example, the table shows that out of the 287 respondents,
171 people answered "Yes" to Q2 (that they order fast food), and out of those 171 people, 125
answered "Yes" to Q4 (that they have visited the restaurants to check cleanliness), 23 answered
"Sometimes" to Q4, and 23 answered "Never" to Q4. Similarly, the table shows that out of the
287 respondents, 116 people answered "No" to Q2 (that they do not order fast food), and out
of those 116 people, 41 answered "Always" to Q4, 22 answered "Sometimes" to Q4, and 53
answered "Never" to Q4. In summary, the table provides information on the frequency of
respondents ordering fast food and whether they have visited the restaurants to check
cleanliness, categorized by their responses to both questions.
Percentage table
Q2 (Do you order fast food?)
Q4 (Have you visited the
restaurants from where you order
food online in order to ascertain
cleanliness of the kitchen and the
staff?)
Yes Sometimes
Never
Always
Total
Yes
44
8
8
60
No
18
8
14
40
62
16
22
100
Total
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Square chi Q2 (Do you order fast food?)
Q4 (Have you visited the
restaurants from where you order
food online in order to ascertain
cleanliness of the kitchen and the
staff?)
Yes Sometimes
Never
Always
Total
Yes
3.38
0.54
6.01
9.93
No
4.99
0.80
8.85
14.64
8.37
1.34
Total
lg column= 2 lg file= 1 total lg=2 Square chi > Square chi 95%=5.99
Ho is rejected. Q4 is not independent of Q2
14.86
24.57
Square chi 24.57
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The above table is a chi-square table that displays the results of a chi-square test for
independence conducted between two questions: Q2 - "Do you order fast food?" and Q4 "Have you visited the restaurants from where you order food online in order to ascertain
cleanliness of the kitchen and the staff?"
The table contains the observed values for each combination of responses, as well as the chisquare values calculated for each cell, row, column, and the total. The row and column totals
are calculated by summing up the observed values in each row and column. The total for the
entire table is the sum of all the observed values. The chi-square value for each cell is
calculated by taking the difference between the observed value and the expected value
(assuming the null hypothesis is true), squaring it, dividing by the expected value, and
summing over all cells. The expected value for each cell is calculated by multiplying the row
and column totals and dividing by the total. The last row and column of the table show the chisquare values for the row and column totals, respectively. The final value in the table is the
total chi-square value. The degrees of freedom for the chi-square test are calculated as (number
of rows - 1) x (number of columns - 1), which in this case is (3 - 1) x (3 - 1) = 4. The results
of the chi-square test indicate that the null hypothesis, which states that there is no relationship
between Q2 and Q4, should be rejected, as the calculated chi-square value (24.57) is greater
than the critical value of 5.99 (at a 95% confidence level) for 4 degrees of freedom. This
suggests that Q4 is not independent of Q2, meaning that there is a relationship between
whether people order fast food and whether they visit the restaurants to check cleanliness. The
finding that Q4 is not independent of Q2 suggests that there is a relationship between whether
people order fast food and whether they visit the restaurants to check cleanliness. This result
may have several implications:
Importance of food safety: The fact that people who order fast food are more likely to visit
restaurants to check cleanliness suggests that they are concerned about food safety. This result
may indicate the importance of food safety to consumers and may imply that fast food
restaurants should take steps to ensure that their kitchens and staff are clean to satisfy these
concerns.
Perception of fast food: The finding that people who order fast food are more likely to visit
restaurants to check cleanliness may suggest that there is a negative perception of fast-food
restaurants. This perception may be due to concerns about food safety or other factors such as
nutrition or environmental impact.
Marketing opportunities: The relationship between Q2 and Q4 may also provide opportunities
for fast food restaurants to market themselves as clean and safe. Restaurants that can
demonstrate their commitment to cleanliness and food safety may be able to attract more
customers who are concerned about these issues.
Policy implications: The finding that Q4 is not independent of Q2 may also have implications
for food safety regulations and policies. Regulators may need to pay special attention to fast
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
food restaurants to ensure that they are maintaining high standards of cleanliness and food
safety. This result may also suggest that consumers would benefit from better access to
information about the cleanliness of fast-food restaurants.
Chi square test shows that visits to online food restaurants in order to check the
cleanliness of the kitchen and staff depend on ordering fast food. The graph shows that
most visits are made when ordering fast food sometimes or always.
-52% who order fast food sometimes or always visit the restaurants.
- 32% who order fast food sometimes or always do not visit the restaurants.
- 16% never order fast food.
Q3 vs Q4
Q3 (Do you order health food?)
Count table
Q4 (Have you visited
the restaurants from
where you order food
online in order to
ascertain cleanliness of
the
kitchen and the
staff?)
I order
I only order Health Food
Health Food a majority
of times
I order
Health food
on a few
occasions
I
never
order
Health
food
Total
Yes
64
41
51
15
171
No
55
19
19
23
116
Total
119
60
70
38
287
The table provided is a count table that displays the number of respondents who answered
"Yes" or "No" to two questions: Q3 - "Do you order health food?" and Q4 - "Have you visited
the restaurants from where you order food online in order to ascertain cleanliness of the kitchen
and the staff?"
The table shows the number of respondents who answered "Yes" or "No" to Q3 for each
response category of Q4. For example, 64 respondents who only order health food also visited
the restaurants to check cleanliness, while 55 respondents who never order health food also
visited the restaurants to check cleanliness.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
The last row and column show the total number of respondents who answered "Yes" or "No"
to each question and the total number of respondents overall.
From the table, we can see that of the 171 respondents who answered "Yes" to Q3, 64 only
order health food, 41 order health food a majority of times, 51 order health food on a few
occasions, and 15 never order health food. Similarly, of the 116 respondents who answered
"No" to Q3, 55 visited the restaurants to check cleanliness and never order health food, 19
visited the restaurants to check cleanliness and order health food a majority of times, 19 visited
the restaurants to check cleanliness and order health food on a few occasions, and 23 never
visited the restaurants to check cleanliness and never order health food.
Overall, the table suggests that there is some relationship between ordering health food and
visiting restaurants to check cleanliness. For example, of the respondents who only order
health food, a majority (64 out of 119) visited the restaurants to check cleanliness. However,
the table does not provide statistical evidence for the strength or significance of this
relationship.
Percentage table Q3 vs Q4 (Do you order health food?)
Percentage table
Q3 (Do you order health food?)
I order
I order Health
Health Food
food on a few
a majority
occasions
of times
I never
order
Health
food
Total
18
5
60
7
7
8
40
21
24
13
100
Q4 (Have you visited the
restaurants from where you
order food online in order to
ascertain cleanliness of the
kitchen and the staff?)
I only order
Health Food
Yes
22
14
No
19
Total
41
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Square chi Q3 (Do you order health food?)
I order
I order
Health Food Health food
a majority
on a few
of times
occasions
I never
order
Health
food
Total
2.07
2.58
6.09
1.14
3.05
3.80
8.98
1.91
5.12
6.38
Square
chi
15.07
Q4 (Have you visited the
restaurants from where you
order food online in order to
ascertain cleanliness of the
kitchen and the staff?)
I only order
Health Food
Yes
0.67
0.77
No
0.99
1.66
Total
15.07
lg column= 3 lg file= 1 total lg=3 Square chi > Square chi 95%=7.82
Ho is rejected. Q4 is not independent of Q3
The table provided is a square chi table that shows the chi-square values for Q3 - "Do you
order health food?" and Q4 - "Have you visited the restaurants from where you order food
online in order to ascertain cleanliness of the kitchen and the staff?" The table displays the
chi-square values for each combination of responses to the two questions. For example, the
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
chi-square value for respondents who only order health food and visit the restaurants to check
cleanliness is 0.67, while the chi-square value for respondents who order health food on a few
occasions and never visit the restaurants to check cleanliness is 2.58. The last row and column
show the total chi-square values for each question and the total chi-square value overall. From
the table, we can see that the total chi-square value is 15.07, which is larger than the critical
value of 7.82 for a 95% confidence level and 3 degrees of freedom. This suggests that there is
a statistically significant relationship between Q3 and Q4, and that Q4 is not independent of
Q3. In other words, the table indicates that there is a significant association between ordering
health food and visiting restaurants to check cleanliness. However, it does not provide
information on the direction or strength of this association.
The implication of the significant association between ordering health food and visiting
restaurants to check cleanliness is that people who are health-conscious are more likely to be
concerned about the cleanliness of the kitchen and staff in restaurants from where they order
food online. This finding suggests that health-conscious individuals are not only concerned
about the nutritional value of their food, but also about the safety and hygiene of the food they
consume. Therefore, restaurants that offer online food ordering services may want to consider
highlighting their cleanliness and safety standards to attract health-conscious customers who
place a premium on these factors. Additionally, food ordering platforms may also want to
provide information about restaurant cleanliness ratings to help customers make informed
decisions about where to order food online. Chi square result test shows that visits to the
restaurants of food online in order to ascertain cleanliness of the kitchen and the staff is
dependent on ordering health food. The graph shows that the majority of visits are made when
ordering mostly or only health food.
37% percent who order only or mostly health food always visit the restaurants. 26% who order
only or mostly health food do not visit the restaurants. 5% who never order fast food, do visit
restaurants. 13% never order fast food.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
10- Q3 vs Q2
Q3 (Do you order health food?)
Count table
Q2 (Do you order
fast food?)
I only
order
Health
Food
Yes Sometimes
76
Never
4
Always
39
I order
Health Food
a majority of
times
40
I order
Health food
on a few
occasions
48
12
8
I never order Total
Health food
14
178
10
19
45
12
5
64
60
70
38
11
9
The table shows the number of respondents who answered 'Yes', 'Sometimes',
'Never', or 'Always' to the question 'Do you order health food?' (Q3) and 'Do you
order fast food?' (Q2). The table is organized into four rows based on the response
to Q3, and four columns based on the response to Q2. The numbers in each cell
represent the number of respondents who fell into that particular combination of
responses. For example, the cell in the first row and first column (76) represents
the number of respondents who answered 'Yes' to Q3 (I only order Health Food)
and 'Sometimes' to Q2 (Do you order fast food?). Similarly, the cell in the last row
and last column (5) represents the number of respondents who answered 'Always'
to Q3 (I never order Health food) and 'I never order Health food' to Q2 (Do you
order fast food?).
Total
Percentage table
Q2 (Do you order
fast food?)
Q3 (Do you order health food?)
I order
I order
I only order
Health
I never order
Health food
Health Food
Food a
Health food
on a few
majority of
occasions
times
287
Total
Yes Sometimes
26
14
17
5
62
Never
1
4
3
7
16
Always
14
3
4
2
22
41
21
24
13
100
Total
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
I order
Q2 (Do you order
fast food?)
I only order
Health Food
Total
I order
Health
Health Food as
food
on
I never order
a Health food
majority of
few
times
Yes Sometimes
0.07
0.48
3.88
0.21
Never
Always
11.52
Square chi table
0.09
28.55
0.71
5.85
17.44
Total
4.64
2.16
40.86
0.83
1.42
10.28
1.41
33.86
3.09
55.78
square chi Q3 (Do you order health food?)
Square 55.78 chi
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
lg column= 3 lg file= 2 total lg=6 Square chi > Square chi 95%=12.60 Ho is rejected. Q3 is not
independent of Q2
The table shows that there is a significant association between ordering health food
and ordering fast food. The Chi-square value of 55.78 exceeds the critical value of
12.60, indicating that the null hypothesis of independence between the two variables
is rejected. Specifically, the table shows that those who never order fast food are
much more likely to never order health food, while those who order fast food
sometimes or always are more likely to order health food at least on occasion. The
table also shows that those who only order health food is less likely to order fast
food than those who order fast food sometimes or always. Overall, the table suggests
that there is a relationship between dietary choices and the frequency of ordering
fast food.
One implication of this outcome is that health-conscious individuals who avoid fast
food are also more likely to choose health food options. This could be useful
information for restaurants and food delivery services, as they may want to offer
more healthy options to attract these customers. On the other hand, individuals who
order fast food more frequently may benefit from education and promotion of
healthy eating options to encourage them to make healthier choices. The results also
suggest that there may be cultural or personal factors influencing dietary choices
that could be further investigated. The chi square result shows that ordering health
food and fast food are not independent. The graph shows that the respondents order
sometime and always fast food considering that they only or mostly order health
food. 40% order health food and consider that they always or sometimes order fast
food. 14% consider that they always order health food and always fast food. 7% do
not order fast food or health food.
Q1 vs Q4
Q1 (How many times do you order food using platforms?)
Count table
Q4 (Have you visited
restaurants from you
order…. cleanliness
...?)
Less than
Between 3
three
and 7 times
times a
a month
month
Between 8
and 15
times a
month
Between 15 Between 30
and 30
and 50
times a
times a
month
month
More
than 50
times a
month
Others Total
No
60
30
9
6
2
0
9
116
Yes
48
56
34
21
4
5
3
171
Total
108
86
43
27
6
5
12
287
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
This table shows the frequency distribution of how many times individuals order food
using online platforms (Q1) and whether they have visited restaurants from where they
order food online to check cleanliness (Q4). The table is presented in a count format.
There are 7 categories for Q1, ranging from "less than three times a month" to "more
than 50 times a month", along with an "Others" category. There are 2 categories for
Q4: "Yes" and "No".
The table shows that out of the 287 individuals surveyed, 171 (59.6%) have visited
restaurants from where they order food online to check cleanliness (Q4 = Yes),
while 116 (40.4%) have not (Q4 = No).
Looking at the relationship between Q1 and Q4, it appears that individuals who
order food using online platforms more frequently are more likely to have visited
restaurants to check cleanliness. For example, among those who order food online
"more than 50 times a month" (n=5), all of them have visited restaurants to check
cleanliness (Q4 = Yes). On the other hand, among those who order food online "less
than three times a month" (n=108), only 48 (44.4%) have visited restaurants to
check cleanliness (Q4 = Yes).
Overall, the table suggests that there may be a relationship between the frequency
of ordering food online and the likelihood of visiting restaurants to check
cleanliness. However, further analysis would be needed to determine the strength
and significance of this relationship.
Percentage table
Q1 (How many times do you order food using platforms?
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Square chi table
Square chi Q1 (How many times do you order food using platforms?)
Q4 (Have you visited
Less than
Between 3
restaurantsfrom you
order…cleanliness
three timesa and 7 timesa
..?)
month
month
Total
Between 8
and 15
times a
month
Between
15 and 30
times a
month
Between
30 and 50
times a
month
More
than 50
times a
month
Others
Total
No
6.12
0.65
4.04
2.21
0.07
2.02
3.55
18.67
Yes
4.15
0.44
2.74
1.50
0.05
1.37
2.41
12.67
10.28
1.09
6.78
3.71
0.13
3.39
5.96
31.34
Square chi
31.34
lg column= 6 lg file= 1 total lg=6 Square chi > Square chi
95%=12,6 Ho is rejected. Q1 is not independent of Q4
The table is showing the relationship between how often someone orders food using
platforms and whether they have visited restaurants to check cleanliness. The chi-
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
square value of 31.34 exceeds the critical value of 12.60, indicating that the null
hypothesis of independence between the two variables is rejected. This means that
there is a significant association between how often someone orders food using
platforms and whether they have visited restaurants to check cleanliness.
Looking at the table, we can see that those who order food using platforms more
frequently (between 8 and 50+ times per month) are more likely to have visited
restaurants to check cleanliness. Those who order food using platforms less frequently
(less than 3 times per month) are less likely to have visited restaurants to check
cleanliness. Additionally, those who have visited restaurants to check cleanliness are
more likely to order food using platforms more frequently.
Overall, the table suggests that there is a relationship between how often someone
orders food using platforms and whether they have visited restaurants to check
cleanliness.
The implications of this outcome suggest that people who use food delivery
platforms more frequently are less likely to visit restaurants to check cleanliness. On
the other hand, those who use food delivery platforms less frequently are more likely
to visit restaurants to check cleanliness. This could have implications for the food
industry, particularly for restaurants that rely heavily on food delivery platforms for
their revenue. Restaurants may need to prioritize cleanliness to attract customers
who use food delivery platforms less frequently and are more likely to visit the
restaurant to check for cleanliness. Additionally, this information could be used to
inform marketing strategies for food delivery platforms to target different segments
of their user base based on their likelihood to visit restaurants to check cleanliness.
The chi square result indicates that visits to restaurants is independent of the
frequency of use of the platform. 16% of participants who order between 3 to 30
times per month do not visit restaurants.
Confidence intervals (95%) were calculated under the following premises:
-The sample was obtained by random sampling and is large enough to be representative
of the population.
The sample size is large enough so that the distribution of the proportion is normal.
The responses behave as dichotomic variables (Y/N).
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Confidence intervals
Column P in the tables below is Muestral
Proprtion Min and Max is Poblational
Proportion
p
Min
Max
Less than three times a month 0.38
0.32
0.43
Between 3 and 7 times a
month
0.30
0.25
0.35
Between 8 and 15 times a
month
0.15
0.11
0.19
Between 15 and 30 times a
month
0.09
0.06
0.13
Between 30 and 50 times a
month
0.02
0.00
0.04
More than 50 times a month 0.02
0.00
0.03
Others
0.04
0.02
0.06
p
Min
Max
Yes Sometimes
0.62
0.56
0.68
Never
0.16
0.11
0.20
Always
0.22
0.17
0.27
Q1
Q2
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
p
Min
Max
I only order Health Food
0.415
0.36
0.47
I order Health Food a majority of times
0.209
0.16
0.26
I order Health food on a few occasions
0.244
0.19
0.29
I never order Health food
0.132
0.09
0.17
Q3
p
Min
Max
No
0.40
0.35
0.46
Yes
0.60
0.54
0.65
Q4
p
Min
Max
Never
0.27
0.21
0.32
Always
0.55
0.49
0.60
Sometimes when it Is declared in the menu
0.19
0.14
0.23
Q5
p
Min
Max
Never
0.22
0.17
0.27
Always
0.60
0.54
0.66
Sometimes
0.18
0.14
0.23
Q6
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
p
Min
Max
Less than 20 years old
0.185
0.14
0.23
Between 20 and 30 old
0.376
0.32
0.43
Between 30 and 40 old
0.303
0.25
0.36
Between 40 and 50 old
0.060
0.03
0.09
Between 50 and 60 years old
0.069
0.04
0.10
above 60
0.014
0.00
0.03
Q7
p
Min
Max
Yes
0.52
0.46
0.58
No
0.35
0.29
0.40
Total intake remains the same 0.09
0.06
0.13
Not Sure
0.03
0.01
0.06
p
Min
Max
No
0.369
0.31
0.42
Yes
0.631
0.58
0.69
Q8
Q9
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
p
Min
Max
No, it has not increased
0.439
0.38
0.50
Have not made an attempt to verify
0.178
0.13
0.22
It has increased by a small percentage
0.230
0.18
0.28
It has increased by a moderate percentage
0.108
0.07
0.14
It has increased significantly
0.045
0.02
0.07
Q10
The confidence intervals of each question indicate the range of possible population
proportions with 95% confidence based on the sample proportions obtained from the
survey.
The sample size is large enough to assume that the distribution of the proportion is
normal. The width of the confidence interval reflects the precision of the estimate,
with narrower intervals indicating more precise estimates.
The minimum and maximum values of the confidence intervals show the range of
possible population proportions, which can be used to make statistical inferences
and comparisons across different questions.
The minimum and maximum values of the confidence interval provide a range of
values within which the true population proportion is expected to fall with a certain
level of confidence (95% in this case). Therefore, we can use this information to
estimate the precision of the sample estimate and the level of uncertainty associated
with it.
For example, for the first question (Q1), the sample proportion for respondents who
consume less than three times a month is 0.32, and the corresponding 95%
confidence interval is [0.38, .43]. This means that we can be 95% confident that the
true proportion of the population who consume less than three times a month falls
between 0.38 and 0.43. The wider the confidence interval, the more uncertain we are
about the true population proportion. On the other hand, a narrower interval indicates
a more precise estimate.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Conclusions:
Pros of Ordering Food Online:
Convenience: Ordering food online can be very convenient as it saves time and effort. You can
browse through a variety of food options from the comfort of your home and place an order at
any time.
Variety: Ordering food online gives you access to a wider variety of food options from
different cuisines and restaurants.
Contactless delivery: During the ongoing COVID-19 pandemic, contactless delivery options
have become more prevalent, which minimizes the risk of exposure to the virus.
Availability of information: Online platforms often provide information about the restaurant,
their hygiene practices, and ingredients used in the food.
Cons of Ordering Food Online:
Quality: The quality of food may not be as good as freshly cooked meals made at home,
especially if the food has been sitting for a while or is not prepared properly.
Reliability: There is always a risk of the food being delayed or cancelled due to unforeseen
circumstances such as traffic or weather conditions. This can be frustrating, especially if you
are hungry and have been waiting for a while.
Hygiene concerns: Although online platforms may provide information about the restaurant's
hygiene practices, there is still a risk of contamination during the preparation and delivery of
food.
Transparency: It can be difficult to determine whether the food is healthy or sugar-free, as the
restaurant may not always list all the ingredients or nutritional information. Pros of HomeCooked Food:
Healthier: Home-cooked food can be healthier as you can control the ingredients and cooking
methods used to prepare the food.
Cost-effective: Cooking at home can be more cost-effective than ordering food online,
especially if you are cooking for multiple people.
Quality control: You have complete control over the quality and freshness of the ingredients
used in your home-cooked meals.
Hygiene: Cooking at home ensures that you are in control of the hygiene practices and
cleanliness of your kitchen.
Cons of Home-Cooked Food:
Time-consuming: Cooking at home can be time-consuming, especially if you have a busy
schedule.
Limited variety: Cooking at home limits the variety of food options available to you. Skill
required: Cooking at home requires some degree of cooking skill and knowledge, which not
everyone may possess.
Ingredients: It may not always be possible to find all the required ingredients for a particular
dish, which can be frustrating.
Insights into Online Food Ordering: A Comprehensive Analysis of
Qualitative and Statistical Survey Results
Acknowledgements:
This report is the culmination of the efforts of a diverse team of contributors, each of whom
played a crucial role in its creation.
At the helm of the project was Srinivasa Gopal, the founder of the Ramanujan Society for
Academic Research and Promotion of Science. He conceptualized and designed the survey,
oversaw the collection of survey results, engaged partners, and brought the report to
completion
Morsel Research and Development Pvt Ltd, Lucknow, our data collection partners, were
responsible for ensuring that the survey was distributed to the right people and that the
responses were collected accurately and securely. Without their assistance, we could not have
gathered the data needed to produce this report.
Glen Edwards owner of Complex Computing based in South Africa, played a vital role in
developing the online survey. His technical knowledge and attention to detail ensured that the
survey was user-friendly and accessible to participants from all over the world.
Finally, we would like to acknowledge the invaluable contribution of Dr Carlos E. Romero L.
Faculty of engineering, Carabobo, University. Valencia - Venezuela, who provided the
statistical analysis of survey results. His expertise in data analysis allowed us to draw
meaningful insights and conclusions from the data collected.
Together, this team of talented individuals worked tirelessly to produce a report that is
informative, accurate, and engaging. We are proud of their contributions and grateful for their
dedication to this project.
About Ramanujan Society:
RAMANUJAN SOCIETY for Academic Research and Promotion of Science is a non-profit
society registered under the Tamil Nadu society registration act with registration number SI
NO: SR/CHENNAI/102/2019